A land use and land cover classification at a 50-m resolution was performed by SarVision as part of the "Master Plan for the Rehabilitation and Revitalization of the Ex-Mega Rice Project Area in Central Kalimantan" (SarVision Netherlands 2008). The classification was based on PALSAR L-band radar data, and using reference data from Landsat satellite imagery, 90-m resolution digital elevation data, MODIS and AATSAR fire hotspot data, land use maps from the Indonesian Ministry of Forestry and Badan Perencana Pembangunan Daerah (BAPPEDA; Indonesian Regional Body for Planning and Development), tree cover percentage map for 2005, ground survey data for 2007-2008, and aerial photographs (SarVision Netherlands 2008). SarVision (2008) note several known inaccuracies of the data, including (a) burnt areas in some cases confused with river-riparian forest, (b) flooded shrubland being poorly defined, (c) tree crops and plantations being under-represented due to similarities in the backscatter signature of shrubland and forest, this includes rubber enrichment areas along rivers, (d) grasslands and ferns confused with shrublands where biomass is particularly high, (e) shrubland classes of different cover percentages being difficult to define(SarVision Netherlands 2008). For this study, a modified typology of land use and land cover types was defined as detailed in Table A1.

Table A1. Land use and land cover descriptions, with simplified classification.

Code

Short description

Long description (SarVision Netherlands 2008)

Simplified classification

1

Riverine-riparian forest (cover >11%)

Riverine, swamp forest and woodland. The main layer consists of broadleaved evergreen closed to open woodland on temporarily flooded land.
Crown cover >11% and tree height up to 40 m. This class is intermediate between freshwater swamp forest on mineral soil and peat swamp forest.
Sometimes forest regrowth in collapsed peat areas may resemble this category and be misclassified as such.

Heath forest (kerangas). Is known to occur in north of block E and near Sebangau NP. Distinctive lowland evergreen broadleaved forest type dominated by small diameter trees with a tree cover >11%, occurring on sandy soils of poor fertility, often subject to water stress (drought or saturation).

Extant forest

21

Tree crops

Includes perennial cash crops and plantations such as acacia, oil palm, tree or shrub cover. Often in mosaic with trees and herbaceous cover.

Areas SarVision identified as (21) located close to the river mouth and identified as coconut region by EMRP "Master Plan" reports.

Agriculture

24

Tree crops – other

Areas SarVision identified as (21), not in coconut areas. Likely to be rubber, oil palm, or acacia.

Agriculture

25

Dryland agriculture – rubber

Dryland agriculture (19) areas that is proximal to rivers on mineral soil, and likely to be rubber mosaics.

Agriculture

26

Dryland agriculture – other

Dryland agriculture (19) areas away from rivers, and likely to be rice dominated.

Agriculture

Key variables used to model the potential of each forest type included elevation, peat depth, distance from rivers and ocean, and a subset of climatic variables (WORLDCLIM, http://www.worldclim.org; Hijmans et al. 2005). Each model was fit using a split sample approach (Guisan and Zimmermann 2000), using a random set of presence points (n = 103 to n = 2221, depending on the extant area of each forest type), and reserving 40% of these for testing the performance of each model. Allocation of each 50m x 50m grid cell to a single forest type was performed on the basis of maximum likelihood (Fig. A1). Approximately 16 percent of the study region could not be allocated to a particular forest type with certainty (i.e., there was overlap of the 95 percent confidence intervals between models), and in such cases the dominant extant forest type was assigned manually. For locations where there was discrepancy between the predicted forest type and the extant forest type (in 17 percent of the study region), the extant forest type was assigned (misclassification between low pole and mixed swamp forest types in intergrade areas accounted for 70 percent of these discrepancies).